Chapter 8: Python Exception Handling

 

Abstract:

Python Exception Handling 

What are exceptions?

Exceptions are errors that occur during the execution of a program.

They can be caused by a variety of factors, such as invalid input, division by zero, or accessing a nonexistent file. 

When an exception occurs, Python creates an exception object and stops the normal flow of the program.

Why handle exceptions?

Exception handling allows you to gracefully handle errors, preventing your program from crashing and providing meaningful feedback to the user.

You can log errors, prompt the user for alternative input, or perform other actions to recover from the error.

How to handle exceptions:

try-except: The core construct for exception handling.

Python

    try:

        # Code that may raise an exception

    except ExceptionType as e:

        # Code to handle the exception

Multiple except: To handle different types of exceptions separately.

Python

    try:

        # Code that may raise an exception

    except ValueError:

        # Handle ValueError

    except IndexError:

        # Handle IndexError

    except Exception:

        # Handle any other exception

else: To execute code if no exception occurs.

Python

    try:

        # Code that may raise an exception

    except Exception:

        # Handle exception

    else:

        # Code to execute if no exception occurs

finally: To execute code regardless of whether an exception occurs.

Python

    try:

        # Code that may raise an exception

    except Exception:

        # Handle exception

    finally:

        # Code to execute regardless of exceptions

raise: To manually raise an exception.

Python

    if condition:

        raise ValueError("Invalid value")

Common Exception Types:

ValueError: Raised when a function receives an argument of the correct type but an inappropriate value.

IndexError: Raised when trying to access an index that doesn't exist in a list or other sequence.

KeyError: Raised when trying to access a key that doesn't exist in a dictionary.

TypeError: Raised when an operation is performed on an object of an inappropriate type.

FileNotFoundError: Raised when trying to open a file that doesn't exist.

ZeroDivisionError: Raised when trying to divide by zero.

Best Practices:

Be specific: Catch specific exceptions whenever possible instead of using a bare except clause.

Log errors: Use a logging library to record errors for debugging.

Fail gracefully: Provide meaningful error messages to the user.

Don't overuse: Use exceptions for exceptional situations, not for normal control flow

Keywords

8. Learn about Regular Expressions & Exception Handling in Python 

Python Exception Handling

User-defined Exception

|

Built-in Exception

Python Try Except

Regular Expression in Python

MongoDB and Python

Learning Outcomes

After undergoing this chapter article you will be able to understand the following:

Python Exception Handling

User-defined Exception

Built-in Exception

Python Try Except

Regular Expression in Python

MongoDB and Python

Chapter 8: Python Exception Handling

8.1 Introduction to Exception Handling

In programming, exceptions are errors that occur during the execution of a program. Python provides robust mechanisms for detecting and responding to such errors, ensuring that programs remain functional and user-friendly even when issues arise.

---

8.2 User-Defined Exceptions

In addition to Python's built-in exceptions, developers can define their own custom exceptions to handle specific scenarios.

Syntax for User-Defined Exceptions:

class CustomException(Exception):
    def __init__(self, message):
        self.message = message
        super().__init__(self.message)

# Example
try:
    raise CustomException("This is a user-defined exception!")
except CustomException as e:
    print(f"Caught an exception: {e}")

Use Case:

User-defined exceptions are useful when you need to enforce custom business rules or constraints. For example, validating user input or ensuring certain conditions in a system.

---

8.3 Built-in Exceptions

Python provides a comprehensive list of built-in exceptions. Commonly used ones include:

• ValueError: Raised when a function gets an argument of the correct type but inappropriate value.
• TypeError: Raised when an operation is performed on an inappropriate type.
• ZeroDivisionError: Raised when division by zero is attempted.
• FileNotFoundError: Raised when a requested file does not exist.

Example:

try:
    number = int("abc")
except ValueError as e:
    print(f"ValueError occurred: {e}")

For a complete list, refer to Python's official documentation.

---

8.4 Python try-except

Python’s try-except block is used to handle exceptions and provide alternate flows when errors occur.

Syntax:

try:
    # Code that may raise an exception
    result = 10 / 0
except ZeroDivisionError as e:
    print("Cannot divide by zero!")
except Exception as e:
    print(f"An error occurred: {e}")
finally:
    print("Execution complete.")

Key Points:

1. finally Block: Runs regardless of whether an exception occurred. Useful for cleanup operations.
2. Multiple except Blocks: Handle different exception types independently.
3. else Block: Executes if no exceptions are raised in the try block.

---

8.5 Regular Expressions in Python

Regular expressions (regex) are a sequence of characters defining search patterns. Python's re module provides powerful tools for regex operations.

Common Functions:

• re.match(): Checks for a match at the beginning of the string.
• re.search(): Searches the entire string for a match.
• re.findall(): Returns all matches as a list.
• re.sub(): Substitutes a part of the string matching a pattern.

Example:

import re

# Match example
pattern = r"\b[A-Za-z]+\b"
text = "This is a test."
matches = re.findall(pattern, text)
print(matches)  # Output: ['This', 'is', 'a', 'test']

Use Case:

Regex is used for data validation, text parsing, and data extraction.

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8.6 MongoDB and Python

MongoDB is a NoSQL database widely used for storing unstructured or semi-structured data. Python interacts with MongoDB through the pymongo library.

Installation:

pip install pymongo

Connecting to MongoDB:

from pymongo import MongoClient

client = MongoClient("mongodb://localhost:27017/")
db = client["mydatabase"]
collection = db["mycollection"]

Basic CRUD Operations:

1. Insert Document:

   document = {"name": "Alice", "age": 25}
   collection.insert_one(document)
   

2. Retrieve Documents:

   for doc in collection.find({"age": {"$gte": 20}}):
       print(doc)
   

3. Update Document:

   collection.update_one({"name": "Alice"}, {"$set": {"age": 26}})
   

4. Delete Document:

   collection.delete_one({"name": "Alice"})
   

Use Case:

MongoDB is ideal for applications that require scalable, high-performance data storage, such as real-time analytics or IoT.

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8.7 Summary

• Exception Handling: Allows handling runtime errors gracefully using try-except.
• User-Defined Exceptions: Custom exceptions for specific scenarios.
• Built-in Exceptions: Predefined error types for common issues.
• Regular Expressions: Useful for string matching and parsing.
• MongoDB with Python: Enables efficient storage and retrieval of unstructured data.

By mastering these concepts, developers can write robust, scalable, and error-resistant Python programs.

8.8. Conclusions

Python exception handling is a crucial aspect of writing robust and reliable code. Here are a few key conclusions about Python exception handling:

Benefits:

Graceful Failure:

Exception handling prevents your program from crashing abruptly when encountering errors. Instead, it allows you to handle errors gracefully, providing informative messages to users and potentially recovering from the error.

Error Isolation:

By catching specific exceptions, you can isolate the source of the problem, making debugging and troubleshooting easier.

Code Readability:

Exception handling constructs like try, except, else, and finally make your code more organized and easier to read.

Flow Control:

While not the primary purpose, exceptions can be used in certain scenarios to alter the flow of your program based on exceptional conditions.

Best Practices:

Be Specific:

Catch only the exceptions you expect to occur in a particular code block. Avoid using a bare except clause, as it can mask unexpected errors.

Handle Exceptions Appropriately:

Don't just silence exceptions. Take appropriate action, such as logging the error, retrying the operation, or providing a fallback mechanism.

Use finally for Cleanup:

The finally block ensures that cleanup code (e.g., closing files, releasing resources) is executed regardless of whether an exception occurred.

Raise Exceptions with Meaningful Messages:

When raising exceptions, provide clear and concise messages that explain the problem and its context.

Define Custom Exceptions:

For specific error conditions in your application, consider defining custom exception classes.

Avoid Using Exceptions for Flow Control:

Exceptions are meant for exceptional situations. Don't use them as a primary means of controlling your program's flow.

Key Takeaways:

Exception handling is essential for writing robust Python code.

Use exception handling to catch and handle errors gracefully, preventing crashes and providing informative feedback to users.

Be specific in your exception handling and avoid using a bare except clause.

Use the finally block for cleanup code that must be executed regardless of exceptions.

Raise exceptions with meaningful messages to aid in debugging and troubleshooting.